NVIDIA driver installation support on GPU instances (#645)

AWS offers Nvidia GPU ready instance type families (P2 and G2).  And, of course Kubernetes supports GPU resource scheduling since 1.6.  However Nvidia drivers is not installed in default coreos ami used in kube-aws.  Then, let's support it!

This implements auto installation support of Nvidia GPU driver. Some driver installation script are borrowed from [/Clarifai/coreos-nvidia](https://github.com/Clarifai/coreos-nvidia/).

## Design summary
### Configuration and what will happen
New configuration for this feature is really simple.  `worker.nodePool[i].gpu.nvidia.{enabled,version}` is introduced in `cluster.yaml`.

- default value of `enabled` is false.
- user will be warned if 
  - user set `enabled: true` when `instanceType` doesn't support GPU.  In this case the configuration will be ignored.
  - user set `enabled: false` when `instanceType` does support GPU
- when `enabled: true` on GPU supported instance type, 
  - nvidia driver will be installed automatically in each node in the nodepool.  
  - The installation will happen just before `kubelet.service` starting (see below).  
  - And, `kubelet` will start with [`--feature-gates="Accelerators=true"`](https://github.com/everpeace/kube-aws/blob/feature/nvidia-gpu/core/controlplane/config/templates/cloud-config-worker#L212-L214)
  - then container can mount nvidia driver [like this](https://gist.github.com/everpeace/9e03050467d5ef5f66b7ce96b5fefa72#file-pod-yaml-L30-L53)
- several tags are assigned to the node for enabling schedule on appropriate GPU model and its driver version by using `nodeAffinity`.
  - `alpha.kubernetes.io/nvidia-gpu-name=<GPU hardware type name>`
  - `kube-aws.coreos.com/gpu=nvidia`,
  - `kube-aws.coreos.com/nvidia-gpu-version=<version>`
  -  Because substitution are not used in unit definition, I introduced `/etc/default/kubectl` for defining these label values in [this commit](5c59944).

### Driver installation process
Most of installation script is borrowed from [/Clarifai/coreos-nvidia](https://github.com/Clarifai/coreos-nvidia/).  Especially, for device node installation, I referenced to Clarifai/coreos-nvidia#4 .  I just described summary of installation process.

- [`kubelet.service`](https://github.com/everpeace/kube-aws/blob/feature/nvidia-gpu/core/controlplane/config/templates/cloud-config-worker#L144-L147) ruires [`nvidia-start.service`](https://github.com/everpeace/kube-aws/blob/feature/nvidia-gpu/core/controlplane/config/templates/cloud-config-worker#L456-L471)
- [`nvidia-start.service`](https://github.com/everpeace/kube-aws/blob/feature/nvidia-gpu/core/controlplane/config/templates/cloud-config-worker#L456-L471)  invokes [`build-and-install.sh`](https://github.com/everpeace/kube-aws/blob/feature/nvidia-gpu/core/controlplane/config/templates/cloud-config-worker#L918-L947), which installs nvidia drivers and kernel module files, via `ExecStartPre`.  `nvidia-start.service` will create device nodes(`nvidiactl` and `nvidia0,1,...`).  Other dynamic device nodes are controlled by`udevadam` (configuration is in [this rule file](https://github.com/everpeace/kube-aws/blob/feature/nvidia-gpu/core/controlplane/config/templates/cloud-config-worker#L905-L939))
  - `nvidia-start.service` is `type=oneshot` because `kubelet.service` should wait until `nvidia-start.sh` completely succeeded.
  - `Restart` policy cannot be used with`type=oneshot`.  `nvidia-start.service` doesn't use systemd's retry feature is not used but manual `retry.sh` is used.
- [nvidia-persistenced](https://docs.nvidia.com/deploy/driver-persistence/#persistence-daemon) is also enabled for speeding up startup.  this service is started/stopped via `udevadam` too.

## How to try
1. build `kube-aws` on this branch
2. `kube-aws up` with minimal nodepool configuration below
   ```
   worker:
    nodePools:
     - name: p2xlarge
       count: 1
       instanceType: p2.xlarge
       rootVolume:
         size: 30
         type: gp2
       gpu:
         nvidia:
           enabled: true
           version: "375.66"
    ```
3.  check `kubectl get nodes --show-labels`.  Then you'll see one node with gpu related labels.
4. try starting this [pod](https://gist.github.com/everpeace/9e03050467d5ef5f66b7ce96b5fefa72#file-pod-yaml)
   ```
   kubectl create -f pod.yaml
   ```
5. log reports sample matrix multiplication is computed on gpus.
   ```
   kubectl logs gpu-pod
   ```

## Full changelog

* add /etc/default/kubelet to worker nodes.

* add nvidia driver installation support.

* add gpu related config test.

* it should be error when user gpu.nvidia.true with GPU unspported intance types.

This change is caused by:
#645 (comment)

* add note which warns that driver may stop working when OS is updated.

This change is caused by:
#645 (comment)

* move nvidia-{start, persisntenced}.service to `coreos.units` section.

creation for nvidia-persistenced user to `users` section, too.

This change is caused by:
#645 (comment)

* introduce unit dependency: kubelet --> nvidia-start --> nvidia-install

deleted `systemctl` command from bash script.  Instead, above unit dependency is introduced.

nvidia-install.service, which just invokes build-and-install.sh is implemented type=oneshot because nvidia-start should wait until nvidia-install.service successed completely.
Enabling retry build-and-install.sh, /opt/nvidia-build/util/retry.sh is introduced.  It is because type=oneshot and Restart=always can't be used in systemd.

* delete nvidia-install.service and now nvidia-start.service invoke build-and-install.sh via ExecStartPre with retry.sh

kubelet.service 'Requires' and 'After' nvidia-star.service.